Mobile health apps have been widely considered in the healthcare sector as innovative channels to reach patients and their families. Accordingly, the aim of the chapter was to investigate factors that influence the customers' adoption of digital health apps in Algeria. The authors adopted an extended technology acceptance model (TAM) framework by integrating the constructs of perceived self-efficacy and trust. A structured questionnaire survey was used to collect data from 186 participants in five cities. Multiple linear regression analysis was used for data analysis. Findings show that perceived usefulness, attitudes, perceived self-efficacy, and perceived ease of use significantly and positively predicted customers' intention to use digital health apps. However, behavioural intention to use was not significantly and positively influenced by trust in digital health system. Moreover, results revealed that the extended TAM explained 60.1% of the variance of intention. The chapter provides valuable results concerning the determinants of adoption of digital health apps.

Drug waste poses a real threat to human health and the environment. Therefore, recycling and sustainability scholars have recently sought practical solutions to the drug waste problem. Furthermore, several governments have made significant efforts to reduce the negative effects of waste, such as establishing programs to take back unwanted drugs (expired and unused) for recycling (i.e., drug reuse or drug redispersing). However, many of these programs have failed to achieve their goals. In this context, it is expected that creating green start-ups to collect unwanted drugs will contribute to solving this problem. Accordingly, this study aims to investigate the antecedents of intentions to create green start-ups for collecting unwanted drugs. To this end, the authors integrate start-up self-efficacy and drug waste collection-related knowledge constructs into the theory of planned behavior (TPB). Using a self-administered paper questionnaire and relying on a convenience sample, data were collected from 328 students in six Algerian universities. A hierarchical multiple regression was conducted to test the proposed study model. Theresults revealed that perceived behavioral control (PBC) (β = 0.187, p < 0.001), attitudes (β = 0.182, p = 0.002), start-up self-efficacy (β = 0.169, p = 0.001), drug waste collection-related knowledge (β = 0.161, p < 0.001), and subjective norms (β = 0.088, p < 0.05) have a positive significant effect on the intention to create a start-up to collect unwanted drugs. In conclusion, this paper contributes to reducing drug waste by investigating the drivers of intention to create green start-ups for collecting unwanted drugs. Therefore, our study is expected to provide valuable insights for hospitals, pharmacies, pharmaceutical manufacturers, environmental protection associations, and stakeholders interested in reverse logistics.

The rapid expansion of digital platforms has significantly influenced consumer purchasing behaviors, particularly in the agri-food sector. Therefore, this paper investigates the key factors driving customers’ intention to use green agri-food delivery apps (GAFDAs) by integrating trust and electronic word of mouth (eWOM) into the Theory of Planned Behavior (TPB) framework. Additionally, this study examines gender as a moderating variable, assessing whether its influence alters the relationships between key determinants and behavioral intention. Data were collected from 252 Algerian consumers, and the proposed model was tested using SmartPLS 4 and SPSS 26.0. The results confirm that attitude, subjective norms, perceived behavioral control (PBC), trust, and eWOM positively and significantly influence the intention to use GAFDAs, with PBC emerging as the strongest predictor. Moreover, gender moderates the effect of trust on behavioral intention, with trust significantly influencing men’s adoption decisions but not those of females. In contrast, subjective norms and PBC are stronger predictors for female consumers. These findings highlight the importance of gender-specific marketing strategies to enhance GAFDA adoption. This study contributes to the literature by extending TPB with trust, eWOM, and gender moderation, offering valuable insights for marketers, policymakers, and app developers promoting sustainable food consumption.

Over recent years, the rate of adoption of artificial intelligence (AI) in the healthcare sector has grown. However, little is known about the success and failure factors. Therefore, this chapter presents a narrative review around the concepts, critical factors, impacts, and challenges behind AI adoption in the healthcare sector. 50 papers were found in the Scopus and Web of Science databases during the period from 2018 to June 2023. The results revealed that the adoption of AI was affected by perceived benefit, perceived ease of use, social influence, attitudes, training, top management support, and more. It was also shown that the challenges of adopting AI are its high cost, unprepared infrastructure, low level of expertise, resistance to change, security concerns, and trust. Consequently, this research advances our theoretical understanding of AI adoption in healthcare organizations in different economic and cultural contexts; and it can provide insights to various stakeholders for effective AI adoption.

COVID-19 caused an increase in the demand for medications, which led to an increase in pharmaceutical waste and there is no doubt that this contributes to environmental pollution. Hence, it became necessary to search for how to protect and improve the environment by encouraging the behavior of medication waste reduction. Accordingly, this study aims to investigate the factors affecting intentions to reduce medication waste. Considering this, we develop an extended theory of planned behavior (TPB) framework by incorporating the constructs of moral obligation, environmental awareness, and medication waste risk perception. Using the convenience sampling method and based on a self-administered questionnaire, a total of 225 usable responses were collected in five Algerian cities. The results showed that positive attitudes (β = 0.316, p < 0.001), moral obligation (β = 0.291, p < 0.001), environmental awareness (β = 0.227, p < 0.001), perceived behavior control (PBC) (β = 0.151, p = 0.001), greater perceived risks (β = 0.127, p < 0.001), and subjective norm (β = 0.096, p < 0.05) significantly and positively influence the medication waste minimization intention. Furthermore, our analyses revealed that the extended TPB model explained 73.40% of the intention variance. In conclusion, we have explored the intentions, and there may be a gap between intent and actual behavior. Therefore, we recommend future studies to examine the factors affecting the actual behavior of medication waste reduction and to investigate environmental ethics and religious commitment as predictors of waste reduction intentions.